A multicomponent prehabilitation pathway to reduce the incidence of delirium in elderly patients in need of major abdominal surgery

__Background:__ Due to the increase in elderly patients who undergo major abdominal surgery there is a subsequent increase in postoperative complications, prolonged hospital stays, health-care costs and mortality rates. Delirium is

Minimizing population health loss due to scarcity in OR capacity: validation of quality of life input

Objectives: A previously developed decision model to prioritize surgical procedures in times of scarce surgical capacity used quality of life (QoL) primarily derived from experts in one center. These estimates are key input of the model, and might be more context-dependent than the other input parameters (age, survival). The aim of this study was to validate our model by replicating these QoL estimates. Methods: The original study estimated QoL of patients in need of commonly performed procedures in live expert-panel meetings. This study replicated this procedure using a web-based Delphi approach in a different hospital. The new QoL scores were compared with the original scores using mixed effects linear regression. The ranking of surgical procedures based on combined QoL values from the validation and original study was compared to the ranking based solely on the original QoL values. Results: The overall mean difference in QoL estimates between the validation study and the original study was − 0.11 (95% CI: -0.12 - -0.10). The model output (DALY/month delay) based on QoL data from both studies was similar to the model output based on the original data only: The Spearman’s correlation coefficient between the ranking of all procedures before and after including the new QoL estimates was 0.988. Discussion: Even though the new QoL estimates were systematically lower than the values from the original study, the ranking for urgency based on health loss per unit of time delay of procedures was consistent. This underscores the robustness and generalizability of the decision model for prioritization of surgical procedures

Minimizing population health loss due to scarcity in OR capacity: validation of quality of life input

Abstract Objectives A previously developed decision model to prioritize surgical procedures in times of scarce surgical capacity used quality of life (QoL) primarily derived from experts in one center. These estimates are key input of the model, and might be more context-dependent than the other input parameters (age, survival). The aim of this study was to validate our model by replicating these QoL estimates. Methods The original study estimated QoL of patients in need of commonly performed procedures in live expert-panel meetings. This study replicated this procedure using a web-based Delphi approach in a different hospital. The new QoL scores were compared with the original scores using mixed effects linear regression. The ranking of surgical procedures based on combined QoL values from the validation and original study was compared to the ranking based solely on the original QoL values. Results The overall mean difference in QoL estimates between the validation study and the original study was − 0.11 (95% CI:  -0.12 - -0.10). The model output (DALY/month delay) based on QoL data from both studies was similar to the model output based on the original data only: The Spearman’s correlation coefficient between the ranking of all procedures before and after including the new QoL estimates was 0.988. Discussion Even though the new QoL estimates were systematically lower than the values from the original study, the ranking for urgency based on health loss per unit of time delay of procedures was consistent. This underscores the robustness and generalizability of the decision model for prioritization of surgical procedures

A multicomponent prehabilitation pathway to reduce the incidence of delirium in elderly patients in need of major abdominal surgery: study protocol for a before-and-after study

Abstract Background Due to the increase in elderly patients who undergo major abdominal surgery there is a subsequent increase in postoperative complications, prolonged hospital stays, health-care costs and mortality rates. Delirium is a frequent and severe complication in the ‘frail’ elderly patient. Different preoperative approaches have been suggested to decrease incidence of delirium by improving patients’ baseline health. Studies implementing these approaches are often heterogeneous, have a small sample and do not provide high-quality or successful strategies. The aim of this study is to prevent postoperative delirium and other complications by implementing a unique multicomponent and multidisciplinary prehabilitation program. Methods This is a single-center controlled before-and-after study. Patients aged ≥70 years in need of surgery for colorectal cancer or an abdominal aortic aneurysm are considered eligible. Baseline characteristics (such as factors of frailty, physical condition and nutritional state) are collected prospectively. During 5 weeks prior to surgery, patients will follow a prehabilitation program to optimize overall health, which includes home-based exercises, dietary advice and intravenous iron infusion in case of anaemia. In case of frailty, a geriatrician will perform a comprehensive geriatric assessment and provide additional preoperative interventions when deemed necessary. The primary outcome is incidence of delirium. Secondary outcomes are length of hospital stay, complication rate, institutionalization, 30-day, 6- and 12-month mortality, mental health and quality of life. Results will be compared to a retrospective control group, meeting the same inclusion and exclusion criteria, operated on between January 2013 and October 2015. Inclusion of the prehabilitation cohort started in November 2015; data collection is ongoing. Discussion This is the first study to investigate the effect of prehabilitation on postoperative delirium. The aim is to provide evidence, based on a large sample size, for a standardized multicomponent strategy to improve patients’ preoperative physical and nutritional status in order to prevent postoperative delirium and other complications. A multimodal intervention was implemented, combining physical, nutritional, mental and hematinic optimization. This research involves a large cohort, including patients most at risk for postoperative adverse outcomes. Trial registration The protocol is retrospectively registered at the Netherlands National Trial Register (NTR) number: NTR5932. Date of registration: 05-04-2016

Capturing postural blood pressure dynamics with near-infrared spectroscopy-measured cerebral oxygenation

Orthostatic hypotension (OH) is highly prevalent in older adults and associated with dizziness, falls, lower physical and cognitive function, cardiovascular disease, and mortality. OH is currently diagnosed in a clinical setting with single-time point cuff measurements. Continuous blood pressure (BP) devices can measure OH dynamics but cannot be used for daily life monitoring. Near-infrared spectroscopy (NIRS) has potential diagnostic value in measuring cerebral oxygenation continuously over a longer time period, but this needs further validation. This study aimed to compare NIRS-measured (cerebral) oxygenation with continuous BP and transcranial Doppler-measured cerebral blood velocity (CBv) during postural changes. This cross-sectional study included 41 participants between 20 and 88 years old. BP, CBv, and cerebral (long channels) and superficial (short channels) oxygenated hemoglobin (O2Hb) were measured continuously during various postural changes. Pearson correlations between BP, CBv, and O2Hb were calculated over curves and specific characteristics (maximum drop amplitude and recovery). BP and O2Hb only showed good curve-based correlations (0.58–0.75) in the initial 30 s after standing up. Early (30–40 s) and 1-min BP recovery associated significantly with O2Hb, but no consistent associations were found for maximum drop amplitude and late (60–175 s) recovery values. Associations between CBv and O2Hb were poor, but stronger for long-channel than short-channel measurements. BP associated well with NIRS-measured O2Hb in the first 30 s after postural change. Stronger associations for CBv with long-channel O2Hb suggest that long-channel NIRS specifically reflects cerebral blood flow during postural transitions, necessary to better understand the consequences of OH such as intolerance symptoms

Correction to: Capturing postural blood pressure dynamics with near‑infrared spectroscopy‑measured cerebral oxygenation (GeroScience, (2023), 10.1007/s11357-023-00791-9)

In the article version originally published online, Table 2 was switched in the publication process. The correct version of Table 2 is shown below. (Table presented.) Heat map of average correlations for supine-stand and sit-stand transitions, during initial response (0-30 seconds after standing up) and late response (30-175 seconds after standing up) * Significantly different (p<0.05) between O2Hb-l and O2Hb-s. SBP Systolic blood pressure; DBP Diastolic blood pressure; MCAv Mean cerebral blood velocity in the middle cerebral artery; O2Hb-l Oxygenated hemoglobin measured with long channels; O2Hb-s Oxygenated hemoglobin measured with short channels; HHb-l Deoxygenated hemoglobin measured with long channels; HHb-s Deoxygenated hemoglobin measured with short channels

Additional file 1 of Minimizing population health loss due to scarcity in OR capacity: validation of quality of life input

Additional file 1: Fig. S1. Calibrated visual analog scale based on the Global burden of disease study. Table S1. Description of input parameters. Table S2. Form for participants in the Delphi rounds in the developmental study

Additional file 3 of Minimizing population health loss due to scarcity in OR capacity: validation of quality of life input

Additional file 3: Fig. S1. The structure of the previously developed cohort state-transition model. Preop: preoperative state; Postop: postoperative state (6). Fig. S2. The model estimates for urgency based on the original quality of life estimates (upper panel) and the updated scores from both the original and the validation study (bottom panel). Fig. S3. The random effects of procedure on the standard deviation of the QoL estimates. These estimates are the random intercept values for procedure in a model with as independent variable the standard deviations of surgical procedures, also including hospital and pre- or postoperative as fixed effects (supplementary table 2). A random intercept above 0 indicates a higher than expected standard deviation, which we interpret as lower consensus between experts. A random intercept below 0 indicates a lower than expected standard deviation, which we interpret as higher consensus between experts. The overall standard deviation of the random effect was 0.005. Table S1. The estimates from the first mixed effects linear regression model. The dependent variable is the utility scores scored by the expert panel. Table S2. The estimates from the second mixed effects linear regression model. The dependent variable is the standard deviation of the utility scores per study center, pre- and postoperative state, and procedure. Table S3. The quality of life estimates and 95% CI derived from the original study and the validation study, stratified for preoperative and postoperative state, corresponding to figure 1 in the manuscript. Table S4. The difference in urgency of surgical procedures between the original and the updated quality of life estimates. Only the diseases which now include the new scores from the validation study are shown. This table corresponds to figure 4 in the manuscript

Additional file 2 of Minimizing population health loss due to scarcity in OR capacity: validation of quality of life input

Additional file 2: Table S1. Descriptions in the Delphi round to introduce the procedures

Minimizing population health loss due to scarcity in OR capacity: validation of quality of life input

Abstract Objectives A previously developed decision model to prioritize surgical procedures in times of scarce surgical capacity used quality of life (QoL) primarily derived from experts in one center. These estimates are key input of the model, and might be more context-dependent than the other input parameters (age, survival). The aim of this study was to validate our model by replicating these QoL estimates. Methods The original study estimated QoL of patients in need of commonly performed procedures in live expert-panel meetings. This study replicated this procedure using a web-based Delphi approach in a different hospital. The new QoL scores were compared with the original scores using mixed effects linear regression. The ranking of surgical procedures based on combined QoL values from the validation and original study was compared to the ranking based solely on the original QoL values. Results The overall mean difference in QoL estimates between the validation study and the original study was − 0.11 (95% CI: -0.12 - -0.10). The model output (DALY/month delay) based on QoL data from both studies was similar to the model output based on the original data only: The Spearman’s correlation coefficient between the ranking of all procedures before and after including the new QoL estimates was 0.988. Discussion Even though the new QoL estimates were systematically lower than the values from the original study, the ranking for urgency based on health loss per unit of time delay of procedures was consistent. This underscores the robustness and generalizability of the decision model for prioritization of surgical procedures